| Issue | #Downvotes for this reason | By |
|---|
| sklearn.svm.classes.SVC(35) | C-Support Vector Classification. The implementation is based on libsvm. The fit time complexity is more than quadratic with the number of samples which makes it hard to scale to dataset with more than a couple of 10000 samples. The multiclass support is handled according to a one-vs-one scheme. For details on the precise mathematical formulation of the provided kernel functions and how `gamma`, `coef0` and `degree` affect each other, see the corresponding section in the narrative documentation: :ref:`svm_kernels`. |
| sklearn.svm.classes.SVC(35)_C | 4955.432744513465 |
| sklearn.svm.classes.SVC(35)_cache_size | 200 |
| sklearn.svm.classes.SVC(35)_class_weight | null |
| sklearn.svm.classes.SVC(35)_coef0 | -0.11355443894096662 |
| sklearn.svm.classes.SVC(35)_decision_function_shape | "ovr" |
| sklearn.svm.classes.SVC(35)_degree | 3 |
| sklearn.svm.classes.SVC(35)_gamma | 0.07570998300814004 |
| sklearn.svm.classes.SVC(35)_kernel | "sigmoid" |
| sklearn.svm.classes.SVC(35)_max_iter | -1 |
| sklearn.svm.classes.SVC(35)_probability | false |
| sklearn.svm.classes.SVC(35)_random_state | 65018 |
| sklearn.svm.classes.SVC(35)_shrinking | false |
| sklearn.svm.classes.SVC(35)_tol | 2.5681726737916055e-05 |
| sklearn.svm.classes.SVC(35)_verbose | false |
0.5 Per class Cross-validation details (10-fold Crossvalidation)
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0.5 Cross-validation details (10-fold Crossvalidation)
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0.5 Cross-validation details (10-fold Crossvalidation)
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2600 Per class Cross-validation details (10-fold Crossvalidation) |
0.5 Cross-validation details (10-fold Crossvalidation)
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1 Cross-validation details (10-fold Crossvalidation)
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0.5 Per class Cross-validation details (10-fold Crossvalidation)
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1 Cross-validation details (10-fold Crossvalidation)
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0.5 Cross-validation details (10-fold Crossvalidation)
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0.7071 Cross-validation details (10-fold Crossvalidation)
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1.4142 Cross-validation details (10-fold Crossvalidation)
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